Ecological Security Pattern Analysis Based on InVEST and Least-Cost Path Model: A Case Study of Dongguan Water Village
The famous “world’s factory” city, Dongguan, like many other places in China, is a typical beneficiary of China’s Reform and Opening-up Policy. However, rapid urban sprawl and economic growth are at the expense of the destruction of the local environment. Therefore, it is of great importance to esta...
Published in: | Sustainability |
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Main Authors: | , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
MDPI AG
2016
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Subjects: | |
Online Access: | https://doi.org/10.3390/su8020172 https://doaj.org/article/a4ca9f9385254e4f991c70d6fbf08814 |
Summary: | The famous “world’s factory” city, Dongguan, like many other places in China, is a typical beneficiary of China’s Reform and Opening-up Policy. However, rapid urban sprawl and economic growth are at the expense of the destruction of the local environment. Therefore, it is of great importance to establish an ecological security network for sustainable development. InVEST models, effective tools to measure sensitivity and intensity of external threats to quantify habitat value, are used to calculate habitat quality of water and land. By combining structural connectivity and the Least-Cost Path model (LCP model), in which corridors are determined based on the minimum accumulative cost path between each critical point, ecological security patterns were calculated. According to the results, the northwest region of Dongguan, having a large quantity of farmlands and water and therefore many corridors and critical patches, is the most essential area in the overall security of ecological environments, which should be protected first. If developed, it should be dominated by eco-tourism and eco-agriculture. We hope that research on the ecological network, which includes critical patches and corridors formed by greenland and rivers, will lead toward better-informed proposals for local urban planning and regional sustainable development. |
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